Toward Ontology Representation and Reasoning for News

Xubo Wen, Xiaoli Ma, Juanzi Li, Jeff Z. Pan, Jiayu Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most research work on news mining nowadays covers phrase and topic level. A few works conducted on logical level mainly focus on personalized news service and no special efforts are put on the applications of ontology techniques on deep news mining. In this paper, we demonstrate a whole strategy for deeply understanding event-focused news taking the advantage of ontology representation and ontology reasoning. We propose an ontology-enriched news deep understanding framework ONDU which addresses the following problems: (1) how to transfer parsed news content into logical triples by using domain ontology. (2) The application of ONDU based on the reasoning results from the ontology reasoner TrOWL over the RDF data expressing the news. Through this whole strategy we can detect the inconsistence among multiple news articles and compare the different information implied in different news. We can even integrate a set of news content through merging the RDF data. The empirical experiment conducted on news from several portals shows the effectiveness and usefulness of our method.
Original languageEnglish
Title of host publicationLinked Data and Knowledge Graph
Subtitle of host publication7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference, CSWS 2013 Shanghai, China, August 2013 Revised Selected Papers
EditorsGuilin Qi, Jie Tang, Jianfeng Du, Jeff Z. Pan, Yong Yu
PublisherSpringer-Verlag
Pages186-198
Number of pages13
ISBN (Electronic)9783642540257
ISBN (Print)9783642540240
DOIs
Publication statusPublished - Nov 2013
Event7th Chinese Semantic Web Symposium and the 2nd Chinese Web ScienceConference, CSWS 2013 - Shanghai, China
Duration: 12 Aug 201316 Aug 2013

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume406
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference7th Chinese Semantic Web Symposium and the 2nd Chinese Web ScienceConference, CSWS 2013
CountryChina
CityShanghai
Period12/08/1316/08/13

Fingerprint

Ontology
Merging
Experiments

Keywords

  • News mining
  • Ontology
  • Reasoning
  • Text understanding
  • TrOWL

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Wen, X., Ma, X., Li, J., Pan, J. Z., & Xie, J. (2013). Toward Ontology Representation and Reasoning for News. In G. Qi, J. Tang, J. Du, J. Z. Pan, & Y. Yu (Eds.), Linked Data and Knowledge Graph: 7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference, CSWS 2013 Shanghai, China, August 2013 Revised Selected Papers (pp. 186-198). (Communications in Computer and Information Science; Vol. 406). Springer-Verlag. https://doi.org/10.1007/978-3-642-54025-7_16

Toward Ontology Representation and Reasoning for News. / Wen, Xubo; Ma, Xiaoli; Li, Juanzi; Pan, Jeff Z.; Xie, Jiayu.

Linked Data and Knowledge Graph: 7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference, CSWS 2013 Shanghai, China, August 2013 Revised Selected Papers. ed. / Guilin Qi; Jie Tang; Jianfeng Du; Jeff Z. Pan; Yong Yu. Springer-Verlag, 2013. p. 186-198 (Communications in Computer and Information Science; Vol. 406).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wen, X, Ma, X, Li, J, Pan, JZ & Xie, J 2013, Toward Ontology Representation and Reasoning for News. in G Qi, J Tang, J Du, JZ Pan & Y Yu (eds), Linked Data and Knowledge Graph: 7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference, CSWS 2013 Shanghai, China, August 2013 Revised Selected Papers. Communications in Computer and Information Science, vol. 406, Springer-Verlag, pp. 186-198, 7th Chinese Semantic Web Symposium and the 2nd Chinese Web ScienceConference, CSWS 2013, Shanghai, China, 12/08/13. https://doi.org/10.1007/978-3-642-54025-7_16
Wen X, Ma X, Li J, Pan JZ, Xie J. Toward Ontology Representation and Reasoning for News. In Qi G, Tang J, Du J, Pan JZ, Yu Y, editors, Linked Data and Knowledge Graph: 7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference, CSWS 2013 Shanghai, China, August 2013 Revised Selected Papers. Springer-Verlag. 2013. p. 186-198. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-54025-7_16
Wen, Xubo ; Ma, Xiaoli ; Li, Juanzi ; Pan, Jeff Z. ; Xie, Jiayu. / Toward Ontology Representation and Reasoning for News. Linked Data and Knowledge Graph: 7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference, CSWS 2013 Shanghai, China, August 2013 Revised Selected Papers. editor / Guilin Qi ; Jie Tang ; Jianfeng Du ; Jeff Z. Pan ; Yong Yu. Springer-Verlag, 2013. pp. 186-198 (Communications in Computer and Information Science).
@inproceedings{1c9e1e9ea0454ea69db0908c21490e36,
title = "Toward Ontology Representation and Reasoning for News",
abstract = "Most research work on news mining nowadays covers phrase and topic level. A few works conducted on logical level mainly focus on personalized news service and no special efforts are put on the applications of ontology techniques on deep news mining. In this paper, we demonstrate a whole strategy for deeply understanding event-focused news taking the advantage of ontology representation and ontology reasoning. We propose an ontology-enriched news deep understanding framework ONDU which addresses the following problems: (1) how to transfer parsed news content into logical triples by using domain ontology. (2) The application of ONDU based on the reasoning results from the ontology reasoner TrOWL over the RDF data expressing the news. Through this whole strategy we can detect the inconsistence among multiple news articles and compare the different information implied in different news. We can even integrate a set of news content through merging the RDF data. The empirical experiment conducted on news from several portals shows the effectiveness and usefulness of our method.",
keywords = "News mining, Ontology, Reasoning, Text understanding, TrOWL",
author = "Xubo Wen and Xiaoli Ma and Juanzi Li and Pan, {Jeff Z.} and Jiayu Xie",
note = "The work is supported by the Natural Science Foundation of China (No. 61035004, No. 60973102), 863 High Technology Program (2011AA01A207), European Union 7th framework project FP7-288342, and THUNUS NExT Co-Lab.",
year = "2013",
month = "11",
doi = "10.1007/978-3-642-54025-7_16",
language = "English",
isbn = "9783642540240",
series = "Communications in Computer and Information Science",
publisher = "Springer-Verlag",
pages = "186--198",
editor = "Guilin Qi and Jie Tang and Jianfeng Du and Pan, {Jeff Z.} and Yong Yu",
booktitle = "Linked Data and Knowledge Graph",

}

TY - GEN

T1 - Toward Ontology Representation and Reasoning for News

AU - Wen, Xubo

AU - Ma, Xiaoli

AU - Li, Juanzi

AU - Pan, Jeff Z.

AU - Xie, Jiayu

N1 - The work is supported by the Natural Science Foundation of China (No. 61035004, No. 60973102), 863 High Technology Program (2011AA01A207), European Union 7th framework project FP7-288342, and THUNUS NExT Co-Lab.

PY - 2013/11

Y1 - 2013/11

N2 - Most research work on news mining nowadays covers phrase and topic level. A few works conducted on logical level mainly focus on personalized news service and no special efforts are put on the applications of ontology techniques on deep news mining. In this paper, we demonstrate a whole strategy for deeply understanding event-focused news taking the advantage of ontology representation and ontology reasoning. We propose an ontology-enriched news deep understanding framework ONDU which addresses the following problems: (1) how to transfer parsed news content into logical triples by using domain ontology. (2) The application of ONDU based on the reasoning results from the ontology reasoner TrOWL over the RDF data expressing the news. Through this whole strategy we can detect the inconsistence among multiple news articles and compare the different information implied in different news. We can even integrate a set of news content through merging the RDF data. The empirical experiment conducted on news from several portals shows the effectiveness and usefulness of our method.

AB - Most research work on news mining nowadays covers phrase and topic level. A few works conducted on logical level mainly focus on personalized news service and no special efforts are put on the applications of ontology techniques on deep news mining. In this paper, we demonstrate a whole strategy for deeply understanding event-focused news taking the advantage of ontology representation and ontology reasoning. We propose an ontology-enriched news deep understanding framework ONDU which addresses the following problems: (1) how to transfer parsed news content into logical triples by using domain ontology. (2) The application of ONDU based on the reasoning results from the ontology reasoner TrOWL over the RDF data expressing the news. Through this whole strategy we can detect the inconsistence among multiple news articles and compare the different information implied in different news. We can even integrate a set of news content through merging the RDF data. The empirical experiment conducted on news from several portals shows the effectiveness and usefulness of our method.

KW - News mining

KW - Ontology

KW - Reasoning

KW - Text understanding

KW - TrOWL

UR - http://www.scopus.com/inward/record.url?scp=84901500791&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-54025-7_16

DO - 10.1007/978-3-642-54025-7_16

M3 - Conference contribution

SN - 9783642540240

T3 - Communications in Computer and Information Science

SP - 186

EP - 198

BT - Linked Data and Knowledge Graph

A2 - Qi, Guilin

A2 - Tang, Jie

A2 - Du, Jianfeng

A2 - Pan, Jeff Z.

A2 - Yu, Yong

PB - Springer-Verlag

ER -